2021
DOI: 10.1016/j.ijheatmasstransfer.2020.120598
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Reduced Order Models for conduction and radiation inside semi-transparent media via the Modal Identification Method

Abstract: In the frame of characterization of thermophysical properties of semi-transparent gray media for which radiative transfers can be modelled by P1 approximation, the present study deals with development, construction and validation of conducto-radiative linear reduced order models (ROMs) explicitly parametrized by thermal conductivity and effective absorption coefficient. As variations of temperature are assumed to be limited in magnitude (about a few tenths of K) in the considered applications, the radiative co… Show more

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Cited by 11 publications
(7 citation statements)
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“…( 81) satisfies the condition (83) when test basis functions are defined by Eq. (84). We use a weight matrix W (Eq.…”
Section: Appendix a Derivation Of Test Basis Functionsmentioning
confidence: 99%
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“…( 81) satisfies the condition (83) when test basis functions are defined by Eq. (84). We use a weight matrix W (Eq.…”
Section: Appendix a Derivation Of Test Basis Functionsmentioning
confidence: 99%
“…ROMs for thermal analysis of spacecraft have been created with POD-Galerkin and trajectory piecewise-linear methods [81]. ROMs for grey nonlinear radiation diffusion problems have been formulated with the PGD [82], POD [83] and modal identification method [84]. A grey ROM for multigroup TRT problems was developed using POD-based representations of frequency averaged opacities and other coefficients [85].…”
Section: Introductionmentioning
confidence: 99%
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“…Numerical methods include three major discretization methods, namely, finite element method (FEM) [14,20,21,22,26], finite difference method (FDM) [18,19,27], and boundary element method (BEM) [54,55,44]. In addition, model reduction techniques [30,31,40,42,43,60] and parallel algorithm [35] have been developed in thermal sciences to handle large and complex discretized thermal systems. In mathematics, the IHCP is called an ill-posed problem in the sense of Hadamard [1].…”
Section: Introductionmentioning
confidence: 99%
“…As in POD-Galerkin, MIM requires the knowledge of the local governing equations. In the MIM approach, the ROM equations may also be written down using a Galerkin projection [14] [18] [19] but only the form of these equations is important. Whereas in POD-Galerkin, the components of the ROM constitutive elements are computed using their literal expressions depending on the space functions obtained from POD, in the MIM these components are identified through a parameter estimation problem corresponding to the minimization of a quadratic functional based on the difference between some reference output data characterizing the system behavior, on the one hand, and the ROM outputs corresponding to the same inputs, on the other hand [15].…”
mentioning
confidence: 99%